Forecasting crop growth, yield and economics with AI powered system using Earth Observation data
The goal of this project is to develop, integrate and demonstrate a scalable prototype of a precision agriculture data analytics platform (FEED) for the Indian agriculture market. FEED will be a “first-of-its-kind” precision agriculture platform for crop growth and yield forecast, fully relying on non-interpolated EO data and crop type and soil reference data (e.g., crop growth models, soil and water requirements databases). The FEED platform will be built using our core innovation in self-learning-based AI powered forecasting engine technology that develops, trains and validates models with BIG DATA from different sources like Earth observation satellites, and databanks of soil, water resources and crops. Our FEED platform will support farmers in their farm management processes in order to help them in achieving maximal yield at a lower cost. FEED will help in optimizing fertilization and lower associated costs to farmers, while minimizing pollution and environmental damage.
Overview
Our prototype will combine a short-to-medium-term intelligent weather forecasting atmospheric module that uses Earth-observation satellite data to forecast local weather conditions with high resolutions. Further, it integrates an irrigation and fertigation schedule module that estimates water and nutrient demands of the targeted crops at each stage of its growth, based on weather and dynamic estimations of crop growth requirements.
